Updated file structure and added predictor.py
Browse filesThis view is limited to 50 files because it contains too many changes. See raw diff
- .gitignore +3 -0
- config.json +1 -1
- config.py +19 -0
- data/model/df_model.csv +0 -0
- tf_model.h5 → data/model/model.h5 +0 -0
- data/model/model2.h5 +3 -0
- data/model/model3.h5 +3 -0
- data/model/model3.ipynb +0 -0
- data/model/my_model_weights.h5 +3 -0
- data/model/my_model_weights2.h5 +3 -0
- data/model/my_model_weights3.h5 +3 -0
- data/preprocessing/UFC_data.ipynb +0 -0
- data/preprocessing/archiv/df_mode_old.csv +0 -0
- data/preprocessing/archiv/df_odds.csv +166 -0
- data/preprocessing/archiv/df_skills.csv +0 -0
- data/preprocessing/archiv/fight_result.csv +0 -0
- data/preprocessing/archiv/fight_with_stats.csv +0 -0
- data/preprocessing/archiv/fight_with_stats_precomp.csv +0 -0
- data/preprocessing/archiv/fighter_details.csv +0 -0
- data/preprocessing/archiv/fighter_total_stats.csv +0 -0
- data/preprocessing/archov/df_model.csv +0 -0
- data/preprocessing/archov/df_skills.csv +0 -0
- data/preprocessing/archov/fight_result.csv +0 -0
- data/preprocessing/archov/fight_with_stats.csv +0 -0
- data/preprocessing/archov/fight_with_stats_precomp1.csv +0 -0
- data/preprocessing/archov/fighter_details.csv +0 -0
- data/preprocessing/archov/fighter_total_stats.csv +0 -0
- data/preprocessing/df_odds.csv +166 -0
- data/preprocessing/df_skills.csv +0 -0
- data/preprocessing/fight_result.csv +0 -0
- data/preprocessing/fight_with_stats.csv +0 -0
- data/preprocessing/fight_with_stats_precomp.csv +0 -0
- data/preprocessing/fighter_details.csv +0 -0
- data/preprocessing/fighter_total_stats.csv +0 -0
- handler.py +36 -15
- predictor.py +148 -0
- preprocessing/UFC_data.ipynb +0 -0
- preprocessing/archiv/df_mode_old.csv +0 -0
- preprocessing/archiv/df_odds.csv +166 -0
- preprocessing/archiv/df_skills.csv +0 -0
- preprocessing/archiv/fight_result.csv +0 -0
- preprocessing/archiv/fight_with_stats.csv +0 -0
- preprocessing/archiv/fight_with_stats_precomp.csv +0 -0
- preprocessing/archiv/fighter_details.csv +0 -0
- preprocessing/archiv/fighter_total_stats.csv +0 -0
- preprocessing/archov/df_model.csv +0 -0
- preprocessing/archov/df_skills.csv +0 -0
- preprocessing/archov/fight_result.csv +0 -0
- preprocessing/archov/fight_with_stats.csv +0 -0
- preprocessing/archov/fight_with_stats_precomp1.csv +0 -0
.gitignore
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.venv/
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__pycache__/
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config.json
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{
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-
"model_type": "
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"input_shape": [null, 200, 89],
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"output_shape": [null, 1],
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"num_layers": 3,
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{
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"model_type": "sequential",
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"input_shape": [null, 200, 89],
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"output_shape": [null, 1],
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"num_layers": 3,
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config.py
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from pathlib import Path
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# Base paths
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ROOT_DIR = Path(__file__).parent
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DATA_DIR = ROOT_DIR / "data"
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# Model paths
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MODEL_PATH = DATA_DIR / "model" / "model.h5"
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# Data paths
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FIGHT_STATS_PATH = DATA_DIR / "preprocessing" / "fight_with_stats_precomp.csv"
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FIGHTER_STATS_PATH = DATA_DIR / "preprocessing" / "fighter_total_stats.csv"
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FIGHTER_DETAILS_PATH = DATA_DIR / "preprocessing" / "fighter_details.csv"
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MODEL_DATA_PATH = DATA_DIR / "model" / "df_model.csv"
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# TensorFlow config
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import os
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os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
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os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0'
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data/model/df_model.csv
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tf_model.h5 → data/model/model.h5
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data/model/model2.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:ed7a99bb0c820ddac4c8be9c437f957ae097e61f3a3e56f1da2ec4570beb289b
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size 943608
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data/model/model3.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:fffe0f1c51af44cf3926b69034fa59c15aef95fdedce9cdb4689459e15bbb7b4
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size 942576
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data/model/model3.ipynb
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data/model/my_model_weights.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:afeaa7a14b17871a666ba03faaafdc4ecaa159ba6ef688eca103331f463032bc
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size 319128
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data/model/my_model_weights2.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:713b36a829644311933b17cb448d85f52e64fccd1471254e4043af375101f4e0
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size 319128
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data/model/my_model_weights3.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:146657604b67644b262ea38cd0c6dcdbe5802a6881af384612ef9145a4c38c6c
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size 319128
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data/preprocessing/UFC_data.ipynb
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data/preprocessing/archiv/df_mode_old.csv
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data/preprocessing/archiv/df_odds.csv
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| 1 |
+
fighter1,fighter2,odds_f1,odds_f2,bookmaker
|
| 2 |
+
Jesus Santos Aguilar,Tatsuro Taira,7.75,1.1,SuperBook
|
| 3 |
+
Jesus Santos Aguilar,Tatsuro Taira,7.5,1.1,Unibet
|
| 4 |
+
Jesus Santos Aguilar,Tatsuro Taira,7.5,1.1,Barstool Sportsbook
|
| 5 |
+
Jesus Santos Aguilar,Tatsuro Taira,9.0,1.08,LowVig.ag
|
| 6 |
+
Jesus Santos Aguilar,Tatsuro Taira,8.5,1.07,Bovada
|
| 7 |
+
Jesus Santos Aguilar,Tatsuro Taira,8.0,1.09,William Hill (US)
|
| 8 |
+
Jesus Santos Aguilar,Tatsuro Taira,7.5,1.1,SugarHouse
|
| 9 |
+
Jesus Santos Aguilar,Tatsuro Taira,7.5,1.1,BetRivers
|
| 10 |
+
Jesus Santos Aguilar,Tatsuro Taira,7.5,1.1,TwinSpires
|
| 11 |
+
Anshul Jubli,Jeka Saragih,1.83,1.97,Barstool Sportsbook
|
| 12 |
+
Anshul Jubli,Jeka Saragih,1.83,1.97,SugarHouse
|
| 13 |
+
Anshul Jubli,Jeka Saragih,1.83,2.0,William Hill (US)
|
| 14 |
+
Anshul Jubli,Jeka Saragih,1.9,1.92,LowVig.ag
|
| 15 |
+
Anshul Jubli,Jeka Saragih,1.83,1.97,BetRivers
|
| 16 |
+
Anshul Jubli,Jeka Saragih,1.83,2.0,SuperBook
|
| 17 |
+
Anshul Jubli,Jeka Saragih,1.83,1.97,Unibet
|
| 18 |
+
Anshul Jubli,Jeka Saragih,1.83,1.97,TwinSpires
|
| 19 |
+
Anshul Jubli,Jeka Saragih,1.87,1.95,DraftKings
|
| 20 |
+
Anshul Jubli,Jeka Saragih,1.87,1.95,Bovada
|
| 21 |
+
Denis Tiuliulin,Jun Yong Park,2.8,1.48,LowVig.ag
|
| 22 |
+
Denis Tiuliulin,Jun Yong Park,2.65,1.51,William Hill (US)
|
| 23 |
+
Denis Tiuliulin,Jun Yong Park,2.75,1.49,DraftKings
|
| 24 |
+
Denis Tiuliulin,Jun Yong Park,2.75,1.5,SuperBook
|
| 25 |
+
Denis Tiuliulin,Jun Yong Park,2.7,1.48,Bovada
|
| 26 |
+
Denis Tiuliulin,Jun Yong Park,2.63,1.49,BetRivers
|
| 27 |
+
Denis Tiuliulin,Jun Yong Park,2.63,1.49,SugarHouse
|
| 28 |
+
Denis Tiuliulin,Jun Yong Park,2.63,1.49,TwinSpires
|
| 29 |
+
Denis Tiuliulin,Jun Yong Park,2.63,1.49,Unibet
|
| 30 |
+
Denis Tiuliulin,Jun Yong Park,2.63,1.49,Barstool Sportsbook
|
| 31 |
+
Hyun Sung Park,Seung Guk Choi,1.51,2.55,Barstool Sportsbook
|
| 32 |
+
Hyun Sung Park,Seung Guk Choi,1.51,2.55,SugarHouse
|
| 33 |
+
Hyun Sung Park,Seung Guk Choi,1.5,2.7,William Hill (US)
|
| 34 |
+
Hyun Sung Park,Seung Guk Choi,1.51,2.55,TwinSpires
|
| 35 |
+
Hyun Sung Park,Seung Guk Choi,1.51,2.55,BetRivers
|
| 36 |
+
Hyun Sung Park,Seung Guk Choi,1.51,2.55,Unibet
|
| 37 |
+
Hyun Sung Park,Seung Guk Choi,1.5,2.55,Bovada
|
| 38 |
+
Hyun Sung Park,Seung Guk Choi,1.55,2.57,LowVig.ag
|
| 39 |
+
Hyun Sung Park,Seung Guk Choi,1.53,2.6,DraftKings
|
| 40 |
+
Jeongyoung Lee,Yi Zha,1.42,3.0,William Hill (US)
|
| 41 |
+
Jeongyoung Lee,Yi Zha,1.4,3.0,SugarHouse
|
| 42 |
+
Jeongyoung Lee,Yi Zha,1.4,3.0,TwinSpires
|
| 43 |
+
Jeongyoung Lee,Yi Zha,1.4,3.0,BetRivers
|
| 44 |
+
Jeongyoung Lee,Yi Zha,1.4,3.0,Barstool Sportsbook
|
| 45 |
+
Jeongyoung Lee,Yi Zha,1.4,3.0,Unibet
|
| 46 |
+
Jeongyoung Lee,Yi Zha,1.4,3.11,LowVig.ag
|
| 47 |
+
Ji Yeon Kim,Mandy Böhm,1.38,3.25,SuperBook
|
| 48 |
+
Ji Yeon Kim,Mandy Böhm,1.35,3.2,Unibet
|
| 49 |
+
Ji Yeon Kim,Mandy Böhm,1.35,3.2,Barstool Sportsbook
|
| 50 |
+
Ji Yeon Kim,Mandy Böhm,1.39,3.15,LowVig.ag
|
| 51 |
+
Ji Yeon Kim,Mandy Böhm,1.39,3.15,DraftKings
|
| 52 |
+
Ji Yeon Kim,Mandy Böhm,1.36,3.12,Bovada
|
| 53 |
+
Ji Yeon Kim,Mandy Böhm,1.38,3.1,William Hill (US)
|
| 54 |
+
Ji Yeon Kim,Mandy Böhm,1.35,3.2,SugarHouse
|
| 55 |
+
Ji Yeon Kim,Mandy Böhm,1.35,3.2,BetRivers
|
| 56 |
+
Ji Yeon Kim,Mandy Böhm,1.35,3.2,TwinSpires
|
| 57 |
+
Adam Fugitt,Yusaku Kinoshita,3.4,1.32,Bovada
|
| 58 |
+
Adam Fugitt,Yusaku Kinoshita,3.2,1.35,SugarHouse
|
| 59 |
+
Adam Fugitt,Yusaku Kinoshita,3.2,1.35,TwinSpires
|
| 60 |
+
Adam Fugitt,Yusaku Kinoshita,3.7,1.31,LowVig.ag
|
| 61 |
+
Adam Fugitt,Yusaku Kinoshita,3.2,1.35,Barstool Sportsbook
|
| 62 |
+
Adam Fugitt,Yusaku Kinoshita,3.2,1.35,BetRivers
|
| 63 |
+
Adam Fugitt,Yusaku Kinoshita,3.3,1.37,SuperBook
|
| 64 |
+
Adam Fugitt,Yusaku Kinoshita,3.2,1.35,Unibet
|
| 65 |
+
Adam Fugitt,Yusaku Kinoshita,3.5,1.33,DraftKings
|
| 66 |
+
Blagoy Ivanov,Marcin Tybura,2.3,1.67,SuperBook
|
| 67 |
+
Blagoy Ivanov,Marcin Tybura,2.26,1.69,LowVig.ag
|
| 68 |
+
Blagoy Ivanov,Marcin Tybura,2.25,1.67,Bovada
|
| 69 |
+
Blagoy Ivanov,Marcin Tybura,2.25,1.64,BetRivers
|
| 70 |
+
Blagoy Ivanov,Marcin Tybura,2.25,1.64,SugarHouse
|
| 71 |
+
Blagoy Ivanov,Marcin Tybura,2.25,1.64,TwinSpires
|
| 72 |
+
Blagoy Ivanov,Marcin Tybura,2.25,1.64,Unibet
|
| 73 |
+
Blagoy Ivanov,Marcin Tybura,2.25,1.64,Barstool Sportsbook
|
| 74 |
+
Da Un Jung,Devin Clark,1.42,3.0,SuperBook
|
| 75 |
+
Da Un Jung,Devin Clark,1.52,2.68,LowVig.ag
|
| 76 |
+
Da Un Jung,Devin Clark,1.47,2.85,DraftKings
|
| 77 |
+
Da Un Jung,Devin Clark,1.45,2.78,Bovada
|
| 78 |
+
Da Un Jung,Devin Clark,1.42,2.88,BetRivers
|
| 79 |
+
Da Un Jung,Devin Clark,1.42,2.88,SugarHouse
|
| 80 |
+
Da Un Jung,Devin Clark,1.42,2.88,TwinSpires
|
| 81 |
+
Da Un Jung,Devin Clark,1.42,2.88,Unibet
|
| 82 |
+
Da Un Jung,Devin Clark,1.42,2.88,Barstool Sportsbook
|
| 83 |
+
Derrick Lewis,Sergey Spivak,2.9,1.45,SuperBook
|
| 84 |
+
Derrick Lewis,Sergey Spivak,2.95,1.43,DraftKings
|
| 85 |
+
Derrick Lewis,Sergey Spivak,2.9,1.38,Bovada
|
| 86 |
+
Derrick Lewis,Sergey Spivak,2.85,1.43,BetRivers
|
| 87 |
+
Derrick Lewis,Sergey Spivak,2.85,1.43,SugarHouse
|
| 88 |
+
Derrick Lewis,Sergey Spivak,2.85,1.43,TwinSpires
|
| 89 |
+
Derrick Lewis,Sergey Spivak,2.85,1.43,Unibet
|
| 90 |
+
Derrick Lewis,Sergey Spivak,2.85,1.43,Barstool Sportsbook
|
| 91 |
+
Dooho Choi,Kyle Nelson,1.54,2.65,SuperBook
|
| 92 |
+
Dooho Choi,Kyle Nelson,1.55,2.57,LowVig.ag
|
| 93 |
+
Dooho Choi,Kyle Nelson,1.53,2.6,DraftKings
|
| 94 |
+
Dooho Choi,Kyle Nelson,1.53,2.55,Bovada
|
| 95 |
+
Dooho Choi,Kyle Nelson,1.55,2.48,BetRivers
|
| 96 |
+
Dooho Choi,Kyle Nelson,1.55,2.48,SugarHouse
|
| 97 |
+
Dooho Choi,Kyle Nelson,1.55,2.48,TwinSpires
|
| 98 |
+
Dooho Choi,Kyle Nelson,1.55,2.48,Unibet
|
| 99 |
+
Dooho Choi,Kyle Nelson,1.55,2.48,Barstool Sportsbook
|
| 100 |
+
Blake Bilder,Shane Young,2.0,1.83,DraftKings
|
| 101 |
+
Blake Bilder,Shane Young,1.97,1.81,MyBookie.ag
|
| 102 |
+
Blake Bilder,Shane Young,2.0,1.83,SuperBook
|
| 103 |
+
Blake Bilder,Shane Young,2.05,1.8,LowVig.ag
|
| 104 |
+
Blake Bilder,Shane Young,1.97,1.82,Barstool Sportsbook
|
| 105 |
+
Blake Bilder,Shane Young,1.97,1.82,TwinSpires
|
| 106 |
+
Blake Bilder,Shane Young,1.97,1.82,SugarHouse
|
| 107 |
+
Blake Bilder,Shane Young,1.97,1.82,BetRivers
|
| 108 |
+
Blake Bilder,Shane Young,1.97,1.82,Unibet
|
| 109 |
+
Justin Tafa,Parker Porter,1.69,2.25,LowVig.ag
|
| 110 |
+
Justin Tafa,Parker Porter,1.71,2.2,DraftKings
|
| 111 |
+
Justin Tafa,Parker Porter,1.66,2.19,MyBookie.ag
|
| 112 |
+
Justin Tafa,Parker Porter,1.69,2.25,SuperBook
|
| 113 |
+
Justin Tafa,Parker Porter,1.67,2.2,Barstool Sportsbook
|
| 114 |
+
Justin Tafa,Parker Porter,1.67,2.2,SugarHouse
|
| 115 |
+
Justin Tafa,Parker Porter,1.67,2.2,TwinSpires
|
| 116 |
+
Justin Tafa,Parker Porter,1.67,2.2,BetRivers
|
| 117 |
+
Justin Tafa,Parker Porter,1.67,2.2,Unibet
|
| 118 |
+
Jack Della Maddalena,Randy Brown,1.33,3.45,LowVig.ag
|
| 119 |
+
Jack Della Maddalena,Randy Brown,1.33,3.55,DraftKings
|
| 120 |
+
Jack Della Maddalena,Randy Brown,1.3,3.41,MyBookie.ag
|
| 121 |
+
Jack Della Maddalena,Randy Brown,1.32,3.6,SuperBook
|
| 122 |
+
Jack Della Maddalena,Randy Brown,1.29,3.65,Barstool Sportsbook
|
| 123 |
+
Jack Della Maddalena,Randy Brown,1.29,3.65,SugarHouse
|
| 124 |
+
Jack Della Maddalena,Randy Brown,1.29,3.65,TwinSpires
|
| 125 |
+
Jack Della Maddalena,Randy Brown,1.29,3.65,BetRivers
|
| 126 |
+
Jack Della Maddalena,Randy Brown,1.29,3.65,Unibet
|
| 127 |
+
Josh Emmett,Yair Rodriguez,2.35,1.65,LowVig.ag
|
| 128 |
+
Josh Emmett,Yair Rodriguez,2.35,1.65,DraftKings
|
| 129 |
+
Josh Emmett,Yair Rodriguez,2.26,1.62,MyBookie.ag
|
| 130 |
+
Josh Emmett,Yair Rodriguez,2.35,1.65,SuperBook
|
| 131 |
+
Josh Emmett,Yair Rodriguez,2.32,1.61,TwinSpires
|
| 132 |
+
Josh Emmett,Yair Rodriguez,2.32,1.61,Barstool Sportsbook
|
| 133 |
+
Josh Emmett,Yair Rodriguez,2.32,1.61,BetRivers
|
| 134 |
+
Josh Emmett,Yair Rodriguez,2.32,1.61,Unibet
|
| 135 |
+
Josh Emmett,Yair Rodriguez,2.32,1.61,SugarHouse
|
| 136 |
+
Alex Volkanovski,Islam Makhachev,3.95,1.28,LowVig.ag
|
| 137 |
+
Alex Volkanovski,Islam Makhachev,3.75,1.28,Barstool Sportsbook
|
| 138 |
+
Alex Volkanovski,Islam Makhachev,3.75,1.28,BetRivers
|
| 139 |
+
Alex Volkanovski,Islam Makhachev,3.75,1.28,Unibet
|
| 140 |
+
Alex Volkanovski,Islam Makhachev,3.75,1.28,TwinSpires
|
| 141 |
+
Alex Volkanovski,Islam Makhachev,3.75,1.28,SugarHouse
|
| 142 |
+
Alex Volkanovski,Islam Makhachev,4.0,1.27,DraftKings
|
| 143 |
+
Alex Volkanovski,Islam Makhachev,3.62,1.28,MyBookie.ag
|
| 144 |
+
Alex Volkanovski,Islam Makhachev,3.9,1.29,SuperBook
|
| 145 |
+
Alexa Grasso,Valentina Shevchenko,5.1,1.17,Barstool Sportsbook
|
| 146 |
+
Alexa Grasso,Valentina Shevchenko,5.1,1.17,TwinSpires
|
| 147 |
+
Alexa Grasso,Valentina Shevchenko,5.25,1.17,LowVig.ag
|
| 148 |
+
Alexa Grasso,Valentina Shevchenko,5.1,1.17,SugarHouse
|
| 149 |
+
Alexa Grasso,Valentina Shevchenko,5.1,1.17,BetRivers
|
| 150 |
+
Ciryl Gane,Jon Jones,2.15,1.74,LowVig.ag
|
| 151 |
+
Ciryl Gane,Jon Jones,2.05,1.8,DraftKings
|
| 152 |
+
Ciryl Gane,Jon Jones,2.1,1.73,Barstool Sportsbook
|
| 153 |
+
Ciryl Gane,Jon Jones,2.1,1.73,BetRivers
|
| 154 |
+
Ciryl Gane,Jon Jones,2.1,1.73,SugarHouse
|
| 155 |
+
Ciryl Gane,Jon Jones,2.1,1.73,TwinSpires
|
| 156 |
+
Kamaru Usman,Leon Edwards,1.41,2.85,Barstool Sportsbook
|
| 157 |
+
Kamaru Usman,Leon Edwards,1.41,2.85,BetRivers
|
| 158 |
+
Kamaru Usman,Leon Edwards,1.41,2.85,SugarHouse
|
| 159 |
+
Kamaru Usman,Leon Edwards,1.41,2.85,TwinSpires
|
| 160 |
+
Kamaru Usman,Leon Edwards,1.41,3.05,DraftKings
|
| 161 |
+
Alex Pereira,Israel Adesanya,2.14,1.71,Barstool Sportsbook
|
| 162 |
+
Alex Pereira,Israel Adesanya,2.14,1.71,BetRivers
|
| 163 |
+
Alex Pereira,Israel Adesanya,2.14,1.71,TwinSpires
|
| 164 |
+
Alex Pereira,Israel Adesanya,2.14,1.71,SugarHouse
|
| 165 |
+
Alex Pereira,Israel Adesanya,2.35,1.65,DraftKings
|
| 166 |
+
Alex Pereira,Israel Adesanya,2.35,1.65,LowVig.ag
|
data/preprocessing/archiv/df_skills.csv
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data/preprocessing/archiv/fight_result.csv
ADDED
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data/preprocessing/archiv/fight_with_stats.csv
ADDED
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data/preprocessing/archiv/fight_with_stats_precomp.csv
ADDED
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data/preprocessing/archiv/fighter_details.csv
ADDED
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data/preprocessing/archiv/fighter_total_stats.csv
ADDED
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data/preprocessing/archov/df_model.csv
ADDED
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data/preprocessing/archov/df_skills.csv
ADDED
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data/preprocessing/archov/fight_result.csv
ADDED
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data/preprocessing/archov/fight_with_stats.csv
ADDED
|
The diff for this file is too large to render.
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|
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data/preprocessing/archov/fight_with_stats_precomp1.csv
ADDED
|
The diff for this file is too large to render.
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data/preprocessing/archov/fighter_details.csv
ADDED
|
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data/preprocessing/archov/fighter_total_stats.csv
ADDED
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data/preprocessing/df_odds.csv
ADDED
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| 1 |
+
fighter1,fighter2,odds_f1,odds_f2,bookmaker
|
| 2 |
+
Jesus Santos Aguilar,Tatsuro Taira,7.75,1.1,SuperBook
|
| 3 |
+
Jesus Santos Aguilar,Tatsuro Taira,7.5,1.1,Unibet
|
| 4 |
+
Jesus Santos Aguilar,Tatsuro Taira,7.5,1.1,Barstool Sportsbook
|
| 5 |
+
Jesus Santos Aguilar,Tatsuro Taira,9.0,1.08,LowVig.ag
|
| 6 |
+
Jesus Santos Aguilar,Tatsuro Taira,8.5,1.07,Bovada
|
| 7 |
+
Jesus Santos Aguilar,Tatsuro Taira,8.0,1.09,William Hill (US)
|
| 8 |
+
Jesus Santos Aguilar,Tatsuro Taira,7.5,1.1,SugarHouse
|
| 9 |
+
Jesus Santos Aguilar,Tatsuro Taira,7.5,1.1,BetRivers
|
| 10 |
+
Jesus Santos Aguilar,Tatsuro Taira,7.5,1.1,TwinSpires
|
| 11 |
+
Anshul Jubli,Jeka Saragih,1.83,1.97,Barstool Sportsbook
|
| 12 |
+
Anshul Jubli,Jeka Saragih,1.83,1.97,SugarHouse
|
| 13 |
+
Anshul Jubli,Jeka Saragih,1.83,2.0,William Hill (US)
|
| 14 |
+
Anshul Jubli,Jeka Saragih,1.9,1.92,LowVig.ag
|
| 15 |
+
Anshul Jubli,Jeka Saragih,1.83,1.97,BetRivers
|
| 16 |
+
Anshul Jubli,Jeka Saragih,1.83,2.0,SuperBook
|
| 17 |
+
Anshul Jubli,Jeka Saragih,1.83,1.97,Unibet
|
| 18 |
+
Anshul Jubli,Jeka Saragih,1.83,1.97,TwinSpires
|
| 19 |
+
Anshul Jubli,Jeka Saragih,1.87,1.95,DraftKings
|
| 20 |
+
Anshul Jubli,Jeka Saragih,1.87,1.95,Bovada
|
| 21 |
+
Denis Tiuliulin,Jun Yong Park,2.8,1.48,LowVig.ag
|
| 22 |
+
Denis Tiuliulin,Jun Yong Park,2.65,1.51,William Hill (US)
|
| 23 |
+
Denis Tiuliulin,Jun Yong Park,2.75,1.49,DraftKings
|
| 24 |
+
Denis Tiuliulin,Jun Yong Park,2.75,1.5,SuperBook
|
| 25 |
+
Denis Tiuliulin,Jun Yong Park,2.7,1.48,Bovada
|
| 26 |
+
Denis Tiuliulin,Jun Yong Park,2.63,1.49,BetRivers
|
| 27 |
+
Denis Tiuliulin,Jun Yong Park,2.63,1.49,SugarHouse
|
| 28 |
+
Denis Tiuliulin,Jun Yong Park,2.63,1.49,TwinSpires
|
| 29 |
+
Denis Tiuliulin,Jun Yong Park,2.63,1.49,Unibet
|
| 30 |
+
Denis Tiuliulin,Jun Yong Park,2.63,1.49,Barstool Sportsbook
|
| 31 |
+
Hyun Sung Park,Seung Guk Choi,1.51,2.55,Barstool Sportsbook
|
| 32 |
+
Hyun Sung Park,Seung Guk Choi,1.51,2.55,SugarHouse
|
| 33 |
+
Hyun Sung Park,Seung Guk Choi,1.5,2.7,William Hill (US)
|
| 34 |
+
Hyun Sung Park,Seung Guk Choi,1.51,2.55,TwinSpires
|
| 35 |
+
Hyun Sung Park,Seung Guk Choi,1.51,2.55,BetRivers
|
| 36 |
+
Hyun Sung Park,Seung Guk Choi,1.51,2.55,Unibet
|
| 37 |
+
Hyun Sung Park,Seung Guk Choi,1.5,2.55,Bovada
|
| 38 |
+
Hyun Sung Park,Seung Guk Choi,1.55,2.57,LowVig.ag
|
| 39 |
+
Hyun Sung Park,Seung Guk Choi,1.53,2.6,DraftKings
|
| 40 |
+
Jeongyoung Lee,Yi Zha,1.42,3.0,William Hill (US)
|
| 41 |
+
Jeongyoung Lee,Yi Zha,1.4,3.0,SugarHouse
|
| 42 |
+
Jeongyoung Lee,Yi Zha,1.4,3.0,TwinSpires
|
| 43 |
+
Jeongyoung Lee,Yi Zha,1.4,3.0,BetRivers
|
| 44 |
+
Jeongyoung Lee,Yi Zha,1.4,3.0,Barstool Sportsbook
|
| 45 |
+
Jeongyoung Lee,Yi Zha,1.4,3.0,Unibet
|
| 46 |
+
Jeongyoung Lee,Yi Zha,1.4,3.11,LowVig.ag
|
| 47 |
+
Ji Yeon Kim,Mandy Böhm,1.38,3.25,SuperBook
|
| 48 |
+
Ji Yeon Kim,Mandy Böhm,1.35,3.2,Unibet
|
| 49 |
+
Ji Yeon Kim,Mandy Böhm,1.35,3.2,Barstool Sportsbook
|
| 50 |
+
Ji Yeon Kim,Mandy Böhm,1.39,3.15,LowVig.ag
|
| 51 |
+
Ji Yeon Kim,Mandy Böhm,1.39,3.15,DraftKings
|
| 52 |
+
Ji Yeon Kim,Mandy Böhm,1.36,3.12,Bovada
|
| 53 |
+
Ji Yeon Kim,Mandy Böhm,1.38,3.1,William Hill (US)
|
| 54 |
+
Ji Yeon Kim,Mandy Böhm,1.35,3.2,SugarHouse
|
| 55 |
+
Ji Yeon Kim,Mandy Böhm,1.35,3.2,BetRivers
|
| 56 |
+
Ji Yeon Kim,Mandy Böhm,1.35,3.2,TwinSpires
|
| 57 |
+
Adam Fugitt,Yusaku Kinoshita,3.4,1.32,Bovada
|
| 58 |
+
Adam Fugitt,Yusaku Kinoshita,3.2,1.35,SugarHouse
|
| 59 |
+
Adam Fugitt,Yusaku Kinoshita,3.2,1.35,TwinSpires
|
| 60 |
+
Adam Fugitt,Yusaku Kinoshita,3.7,1.31,LowVig.ag
|
| 61 |
+
Adam Fugitt,Yusaku Kinoshita,3.2,1.35,Barstool Sportsbook
|
| 62 |
+
Adam Fugitt,Yusaku Kinoshita,3.2,1.35,BetRivers
|
| 63 |
+
Adam Fugitt,Yusaku Kinoshita,3.3,1.37,SuperBook
|
| 64 |
+
Adam Fugitt,Yusaku Kinoshita,3.2,1.35,Unibet
|
| 65 |
+
Adam Fugitt,Yusaku Kinoshita,3.5,1.33,DraftKings
|
| 66 |
+
Blagoy Ivanov,Marcin Tybura,2.3,1.67,SuperBook
|
| 67 |
+
Blagoy Ivanov,Marcin Tybura,2.26,1.69,LowVig.ag
|
| 68 |
+
Blagoy Ivanov,Marcin Tybura,2.25,1.67,Bovada
|
| 69 |
+
Blagoy Ivanov,Marcin Tybura,2.25,1.64,BetRivers
|
| 70 |
+
Blagoy Ivanov,Marcin Tybura,2.25,1.64,SugarHouse
|
| 71 |
+
Blagoy Ivanov,Marcin Tybura,2.25,1.64,TwinSpires
|
| 72 |
+
Blagoy Ivanov,Marcin Tybura,2.25,1.64,Unibet
|
| 73 |
+
Blagoy Ivanov,Marcin Tybura,2.25,1.64,Barstool Sportsbook
|
| 74 |
+
Da Un Jung,Devin Clark,1.42,3.0,SuperBook
|
| 75 |
+
Da Un Jung,Devin Clark,1.52,2.68,LowVig.ag
|
| 76 |
+
Da Un Jung,Devin Clark,1.47,2.85,DraftKings
|
| 77 |
+
Da Un Jung,Devin Clark,1.45,2.78,Bovada
|
| 78 |
+
Da Un Jung,Devin Clark,1.42,2.88,BetRivers
|
| 79 |
+
Da Un Jung,Devin Clark,1.42,2.88,SugarHouse
|
| 80 |
+
Da Un Jung,Devin Clark,1.42,2.88,TwinSpires
|
| 81 |
+
Da Un Jung,Devin Clark,1.42,2.88,Unibet
|
| 82 |
+
Da Un Jung,Devin Clark,1.42,2.88,Barstool Sportsbook
|
| 83 |
+
Derrick Lewis,Sergey Spivak,2.9,1.45,SuperBook
|
| 84 |
+
Derrick Lewis,Sergey Spivak,2.95,1.43,DraftKings
|
| 85 |
+
Derrick Lewis,Sergey Spivak,2.9,1.38,Bovada
|
| 86 |
+
Derrick Lewis,Sergey Spivak,2.85,1.43,BetRivers
|
| 87 |
+
Derrick Lewis,Sergey Spivak,2.85,1.43,SugarHouse
|
| 88 |
+
Derrick Lewis,Sergey Spivak,2.85,1.43,TwinSpires
|
| 89 |
+
Derrick Lewis,Sergey Spivak,2.85,1.43,Unibet
|
| 90 |
+
Derrick Lewis,Sergey Spivak,2.85,1.43,Barstool Sportsbook
|
| 91 |
+
Dooho Choi,Kyle Nelson,1.54,2.65,SuperBook
|
| 92 |
+
Dooho Choi,Kyle Nelson,1.55,2.57,LowVig.ag
|
| 93 |
+
Dooho Choi,Kyle Nelson,1.53,2.6,DraftKings
|
| 94 |
+
Dooho Choi,Kyle Nelson,1.53,2.55,Bovada
|
| 95 |
+
Dooho Choi,Kyle Nelson,1.55,2.48,BetRivers
|
| 96 |
+
Dooho Choi,Kyle Nelson,1.55,2.48,SugarHouse
|
| 97 |
+
Dooho Choi,Kyle Nelson,1.55,2.48,TwinSpires
|
| 98 |
+
Dooho Choi,Kyle Nelson,1.55,2.48,Unibet
|
| 99 |
+
Dooho Choi,Kyle Nelson,1.55,2.48,Barstool Sportsbook
|
| 100 |
+
Blake Bilder,Shane Young,2.0,1.83,DraftKings
|
| 101 |
+
Blake Bilder,Shane Young,1.97,1.81,MyBookie.ag
|
| 102 |
+
Blake Bilder,Shane Young,2.0,1.83,SuperBook
|
| 103 |
+
Blake Bilder,Shane Young,2.05,1.8,LowVig.ag
|
| 104 |
+
Blake Bilder,Shane Young,1.97,1.82,Barstool Sportsbook
|
| 105 |
+
Blake Bilder,Shane Young,1.97,1.82,TwinSpires
|
| 106 |
+
Blake Bilder,Shane Young,1.97,1.82,SugarHouse
|
| 107 |
+
Blake Bilder,Shane Young,1.97,1.82,BetRivers
|
| 108 |
+
Blake Bilder,Shane Young,1.97,1.82,Unibet
|
| 109 |
+
Justin Tafa,Parker Porter,1.69,2.25,LowVig.ag
|
| 110 |
+
Justin Tafa,Parker Porter,1.71,2.2,DraftKings
|
| 111 |
+
Justin Tafa,Parker Porter,1.66,2.19,MyBookie.ag
|
| 112 |
+
Justin Tafa,Parker Porter,1.69,2.25,SuperBook
|
| 113 |
+
Justin Tafa,Parker Porter,1.67,2.2,Barstool Sportsbook
|
| 114 |
+
Justin Tafa,Parker Porter,1.67,2.2,SugarHouse
|
| 115 |
+
Justin Tafa,Parker Porter,1.67,2.2,TwinSpires
|
| 116 |
+
Justin Tafa,Parker Porter,1.67,2.2,BetRivers
|
| 117 |
+
Justin Tafa,Parker Porter,1.67,2.2,Unibet
|
| 118 |
+
Jack Della Maddalena,Randy Brown,1.33,3.45,LowVig.ag
|
| 119 |
+
Jack Della Maddalena,Randy Brown,1.33,3.55,DraftKings
|
| 120 |
+
Jack Della Maddalena,Randy Brown,1.3,3.41,MyBookie.ag
|
| 121 |
+
Jack Della Maddalena,Randy Brown,1.32,3.6,SuperBook
|
| 122 |
+
Jack Della Maddalena,Randy Brown,1.29,3.65,Barstool Sportsbook
|
| 123 |
+
Jack Della Maddalena,Randy Brown,1.29,3.65,SugarHouse
|
| 124 |
+
Jack Della Maddalena,Randy Brown,1.29,3.65,TwinSpires
|
| 125 |
+
Jack Della Maddalena,Randy Brown,1.29,3.65,BetRivers
|
| 126 |
+
Jack Della Maddalena,Randy Brown,1.29,3.65,Unibet
|
| 127 |
+
Josh Emmett,Yair Rodriguez,2.35,1.65,LowVig.ag
|
| 128 |
+
Josh Emmett,Yair Rodriguez,2.35,1.65,DraftKings
|
| 129 |
+
Josh Emmett,Yair Rodriguez,2.26,1.62,MyBookie.ag
|
| 130 |
+
Josh Emmett,Yair Rodriguez,2.35,1.65,SuperBook
|
| 131 |
+
Josh Emmett,Yair Rodriguez,2.32,1.61,TwinSpires
|
| 132 |
+
Josh Emmett,Yair Rodriguez,2.32,1.61,Barstool Sportsbook
|
| 133 |
+
Josh Emmett,Yair Rodriguez,2.32,1.61,BetRivers
|
| 134 |
+
Josh Emmett,Yair Rodriguez,2.32,1.61,Unibet
|
| 135 |
+
Josh Emmett,Yair Rodriguez,2.32,1.61,SugarHouse
|
| 136 |
+
Alex Volkanovski,Islam Makhachev,3.95,1.28,LowVig.ag
|
| 137 |
+
Alex Volkanovski,Islam Makhachev,3.75,1.28,Barstool Sportsbook
|
| 138 |
+
Alex Volkanovski,Islam Makhachev,3.75,1.28,BetRivers
|
| 139 |
+
Alex Volkanovski,Islam Makhachev,3.75,1.28,Unibet
|
| 140 |
+
Alex Volkanovski,Islam Makhachev,3.75,1.28,TwinSpires
|
| 141 |
+
Alex Volkanovski,Islam Makhachev,3.75,1.28,SugarHouse
|
| 142 |
+
Alex Volkanovski,Islam Makhachev,4.0,1.27,DraftKings
|
| 143 |
+
Alex Volkanovski,Islam Makhachev,3.62,1.28,MyBookie.ag
|
| 144 |
+
Alex Volkanovski,Islam Makhachev,3.9,1.29,SuperBook
|
| 145 |
+
Alexa Grasso,Valentina Shevchenko,5.1,1.17,Barstool Sportsbook
|
| 146 |
+
Alexa Grasso,Valentina Shevchenko,5.1,1.17,TwinSpires
|
| 147 |
+
Alexa Grasso,Valentina Shevchenko,5.25,1.17,LowVig.ag
|
| 148 |
+
Alexa Grasso,Valentina Shevchenko,5.1,1.17,SugarHouse
|
| 149 |
+
Alexa Grasso,Valentina Shevchenko,5.1,1.17,BetRivers
|
| 150 |
+
Ciryl Gane,Jon Jones,2.15,1.74,LowVig.ag
|
| 151 |
+
Ciryl Gane,Jon Jones,2.05,1.8,DraftKings
|
| 152 |
+
Ciryl Gane,Jon Jones,2.1,1.73,Barstool Sportsbook
|
| 153 |
+
Ciryl Gane,Jon Jones,2.1,1.73,BetRivers
|
| 154 |
+
Ciryl Gane,Jon Jones,2.1,1.73,SugarHouse
|
| 155 |
+
Ciryl Gane,Jon Jones,2.1,1.73,TwinSpires
|
| 156 |
+
Kamaru Usman,Leon Edwards,1.41,2.85,Barstool Sportsbook
|
| 157 |
+
Kamaru Usman,Leon Edwards,1.41,2.85,BetRivers
|
| 158 |
+
Kamaru Usman,Leon Edwards,1.41,2.85,SugarHouse
|
| 159 |
+
Kamaru Usman,Leon Edwards,1.41,2.85,TwinSpires
|
| 160 |
+
Kamaru Usman,Leon Edwards,1.41,3.05,DraftKings
|
| 161 |
+
Alex Pereira,Israel Adesanya,2.14,1.71,Barstool Sportsbook
|
| 162 |
+
Alex Pereira,Israel Adesanya,2.14,1.71,BetRivers
|
| 163 |
+
Alex Pereira,Israel Adesanya,2.14,1.71,TwinSpires
|
| 164 |
+
Alex Pereira,Israel Adesanya,2.14,1.71,SugarHouse
|
| 165 |
+
Alex Pereira,Israel Adesanya,2.35,1.65,DraftKings
|
| 166 |
+
Alex Pereira,Israel Adesanya,2.35,1.65,LowVig.ag
|
data/preprocessing/df_skills.csv
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
data/preprocessing/fight_result.csv
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
data/preprocessing/fight_with_stats.csv
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
data/preprocessing/fight_with_stats_precomp.csv
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
data/preprocessing/fighter_details.csv
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
data/preprocessing/fighter_total_stats.csv
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
handler.py
CHANGED
|
@@ -1,19 +1,28 @@
|
|
| 1 |
import tensorflow as tf
|
| 2 |
-
import numpy as np
|
| 3 |
from typing import Dict, Any
|
|
|
|
|
|
|
| 4 |
|
| 5 |
|
| 6 |
class CustomLSTM(tf.keras.layers.LSTM):
|
| 7 |
-
|
| 8 |
-
|
| 9 |
-
|
|
|
|
|
|
|
|
|
|
| 10 |
|
| 11 |
|
| 12 |
class EndpointHandler:
|
| 13 |
-
def __init__(self
|
| 14 |
-
#
|
| 15 |
tf.keras.utils.get_custom_objects()['LSTM'] = CustomLSTM
|
| 16 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 17 |
|
| 18 |
def __call__(self, data: Dict[str, Any]) -> Dict[str, Any]:
|
| 19 |
"""
|
|
@@ -33,12 +42,24 @@ class EndpointHandler:
|
|
| 33 |
if not fighter1 or not fighter2:
|
| 34 |
return {"error": "Both 'fighter1' and 'fighter2' must be provided."}
|
| 35 |
|
| 36 |
-
|
| 37 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 38 |
|
| 39 |
-
|
| 40 |
-
|
| 41 |
-
|
| 42 |
-
|
| 43 |
-
|
| 44 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
import tensorflow as tf
|
|
|
|
| 2 |
from typing import Dict, Any
|
| 3 |
+
from predictor import FightPredictor
|
| 4 |
+
from config import MODEL_PATH
|
| 5 |
|
| 6 |
|
| 7 |
class CustomLSTM(tf.keras.layers.LSTM):
|
| 8 |
+
"""Custom LSTM layer that removes time_major from kwargs"""
|
| 9 |
+
@classmethod
|
| 10 |
+
def from_config(cls, config):
|
| 11 |
+
# Remove time_major if present in config
|
| 12 |
+
config.pop('time_major', None)
|
| 13 |
+
return super().from_config(config)
|
| 14 |
|
| 15 |
|
| 16 |
class EndpointHandler:
|
| 17 |
+
def __init__(self):
|
| 18 |
+
# Register the custom layer
|
| 19 |
tf.keras.utils.get_custom_objects()['LSTM'] = CustomLSTM
|
| 20 |
+
|
| 21 |
+
# Load model using path from config
|
| 22 |
+
self.model = tf.keras.models.load_model(str(MODEL_PATH))
|
| 23 |
+
|
| 24 |
+
# Initialize predictor
|
| 25 |
+
self.predictor = FightPredictor(self.model)
|
| 26 |
|
| 27 |
def __call__(self, data: Dict[str, Any]) -> Dict[str, Any]:
|
| 28 |
"""
|
|
|
|
| 42 |
if not fighter1 or not fighter2:
|
| 43 |
return {"error": "Both 'fighter1' and 'fighter2' must be provided."}
|
| 44 |
|
| 45 |
+
try:
|
| 46 |
+
# Get prediction using FightPredictor
|
| 47 |
+
f1_prob, f2_prob, details = self.predictor.get_prediction(
|
| 48 |
+
fighter1,
|
| 49 |
+
fighter2,
|
| 50 |
+
verbose=True
|
| 51 |
+
)
|
| 52 |
+
|
| 53 |
+
if f1_prob is None:
|
| 54 |
+
return {"error": "Prediction failed"}
|
| 55 |
|
| 56 |
+
return {
|
| 57 |
+
"fighter1": fighter1,
|
| 58 |
+
"fighter2": fighter2,
|
| 59 |
+
"fighter1_win_probability": f1_prob,
|
| 60 |
+
"fighter2_win_probability": f2_prob,
|
| 61 |
+
"details": details
|
| 62 |
+
}
|
| 63 |
+
|
| 64 |
+
except Exception as e:
|
| 65 |
+
return {"error": str(e)}
|
predictor.py
ADDED
|
@@ -0,0 +1,148 @@
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
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|
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|
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|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import numpy as np
|
| 2 |
+
import pandas as pd
|
| 3 |
+
from sklearn.preprocessing import MinMaxScaler
|
| 4 |
+
from typing import Tuple, Dict, Optional
|
| 5 |
+
import pandas as pd
|
| 6 |
+
|
| 7 |
+
from config import (
|
| 8 |
+
FIGHT_STATS_PATH,
|
| 9 |
+
FIGHTER_STATS_PATH,
|
| 10 |
+
FIGHTER_DETAILS_PATH,
|
| 11 |
+
MODEL_DATA_PATH
|
| 12 |
+
)
|
| 13 |
+
|
| 14 |
+
class FightPredictor:
|
| 15 |
+
def __init__(self, model):
|
| 16 |
+
self.model = model
|
| 17 |
+
self._load_data()
|
| 18 |
+
|
| 19 |
+
def _load_data(self):
|
| 20 |
+
"""Load required datasets"""
|
| 21 |
+
self.df = pd.read_csv(FIGHT_STATS_PATH)
|
| 22 |
+
self.df_fighters = pd.read_csv(FIGHTER_STATS_PATH)
|
| 23 |
+
self.df_fighters_details = pd.read_csv(FIGHTER_DETAILS_PATH, parse_dates=['DOB'])
|
| 24 |
+
self.df_model = pd.read_csv(MODEL_DATA_PATH, parse_dates=True)
|
| 25 |
+
|
| 26 |
+
# Calculate ages
|
| 27 |
+
today = pd.Timestamp.today()
|
| 28 |
+
self.df_fighters_details['AGE'] = self.df_fighters_details['DOB'].apply(
|
| 29 |
+
lambda x: (today - pd.Timestamp(x)).days / 365.25
|
| 30 |
+
).round(1)
|
| 31 |
+
|
| 32 |
+
def _validate_fighters(self, f1: str, f2: str):
|
| 33 |
+
"""Validate that both fighters exist in dataset"""
|
| 34 |
+
for fighter in [f1, f2]:
|
| 35 |
+
if fighter not in self.df_fighters['FIGHTER'].values:
|
| 36 |
+
raise ValueError(f"Fighter '{fighter}' not found in database")
|
| 37 |
+
|
| 38 |
+
def _get_fighter_stats(self, f1: str, f2: str, verbose: bool) -> Tuple[np.ndarray, Dict]:
|
| 39 |
+
"""Get fighter statistics and compute input features"""
|
| 40 |
+
f1_df = self.df_fighters.loc[self.df_fighters['FIGHTER'] == f1]
|
| 41 |
+
f2_df = self.df_fighters.loc[self.df_fighters['FIGHTER'] == f2]
|
| 42 |
+
|
| 43 |
+
# Compute age difference
|
| 44 |
+
agediff = (
|
| 45 |
+
self.df_fighters_details[self.df_fighters_details['FIGHTER'] == f1]['AGE'].values[0] -
|
| 46 |
+
self.df_fighters_details[self.df_fighters_details['FIGHTER'] == f2]['AGE'].values[0]
|
| 47 |
+
)
|
| 48 |
+
|
| 49 |
+
# Collect form scores and fight stats
|
| 50 |
+
form_scores = [f1_df['form_skore_fighter'].values[0], f2_df['form_skore_fighter'].values[0]]
|
| 51 |
+
no_of_fights = [f1_df['Fights'].values[0], f2_df['Fights'].values[0]]
|
| 52 |
+
W_D_NC = (
|
| 53 |
+
f1_df[['Win', 'DRAW', 'No_contest']].values.tolist()[0] +
|
| 54 |
+
f2_df[['Win', 'DRAW', 'No_contest']].values.tolist()[0]
|
| 55 |
+
)
|
| 56 |
+
|
| 57 |
+
# Process stats
|
| 58 |
+
stats_f1, stats_f2 = [], []
|
| 59 |
+
for col in self.df_fighters.columns[10:]:
|
| 60 |
+
splited = col.split('_')
|
| 61 |
+
if 'CTRL' in splited:
|
| 62 |
+
stats_f1.append((f1_df[col] / f1_df['TotalTime']).values[0])
|
| 63 |
+
stats_f2.append((f2_df[col] / f2_df['TotalTime']).values[0])
|
| 64 |
+
if 'attemps' in splited:
|
| 65 |
+
stats_f1.append((f1_df[col.replace('attemps', 'landed')] / f1_df[col]).values[0])
|
| 66 |
+
stats_f1.append((f1_df[col.replace('attemps', 'landed')] / f1_df['TotalTime']).values[0] * 300)
|
| 67 |
+
stats_f2.append((f2_df[col.replace('attemps', 'landed')] / f2_df[col]).values[0])
|
| 68 |
+
stats_f2.append((f2_df[col.replace('attemps', 'landed')] / f2_df['TotalTime']).values[0] * 300)
|
| 69 |
+
|
| 70 |
+
stats_list = stats_f1 + stats_f2
|
| 71 |
+
|
| 72 |
+
# Prepare input array
|
| 73 |
+
vstup = np.array([1] +
|
| 74 |
+
[f1_df.iloc[0][col] - f2_df.iloc[0][col] for col in ['HEIGHT_fighter', 'REACH_fighter']] +
|
| 75 |
+
[agediff] + form_scores + no_of_fights + W_D_NC + stats_list
|
| 76 |
+
)
|
| 77 |
+
|
| 78 |
+
# Prepare details dict if verbose
|
| 79 |
+
details = {}
|
| 80 |
+
if verbose:
|
| 81 |
+
details = {
|
| 82 |
+
"age_difference": f"{agediff:.1f}",
|
| 83 |
+
f"{f1}_form_score": f"{form_scores[0]:.2f}",
|
| 84 |
+
f"{f2}_form_score": f"{form_scores[1]:.2f}",
|
| 85 |
+
f"{f1}_total_fights": int(no_of_fights[0]),
|
| 86 |
+
f"{f2}_total_fights": int(no_of_fights[1])
|
| 87 |
+
}
|
| 88 |
+
|
| 89 |
+
return vstup, details
|
| 90 |
+
|
| 91 |
+
def _scale_input(self, vstup: np.ndarray) -> np.ndarray:
|
| 92 |
+
"""Scale input features"""
|
| 93 |
+
scaler = MinMaxScaler(feature_range=(0, 1))
|
| 94 |
+
combined_df = pd.concat(
|
| 95 |
+
[self.df_model, pd.DataFrame([vstup], columns=self.df_model.columns)],
|
| 96 |
+
ignore_index=True
|
| 97 |
+
)
|
| 98 |
+
vstup_scaled = scaler.fit_transform(combined_df.iloc[:, 1:])[-200:, :]
|
| 99 |
+
return np.nan_to_num(vstup_scaled)
|
| 100 |
+
|
| 101 |
+
def get_prediction(self, f1: str, f2: str, verbose: bool = False) -> Optional[Tuple[float, float, Dict]]:
|
| 102 |
+
"""
|
| 103 |
+
Generate fight prediction between two fighters
|
| 104 |
+
|
| 105 |
+
Args:
|
| 106 |
+
f1: Name of first fighter
|
| 107 |
+
f2: Name of second fighter
|
| 108 |
+
verbose: Whether to return additional details
|
| 109 |
+
|
| 110 |
+
Returns:
|
| 111 |
+
Tuple of (fighter1_win_probability, fighter2_win_probability, details_dict)
|
| 112 |
+
Returns None if prediction fails
|
| 113 |
+
"""
|
| 114 |
+
try:
|
| 115 |
+
# Validate fighters exist
|
| 116 |
+
self._validate_fighters(f1, f2)
|
| 117 |
+
|
| 118 |
+
# Get fighter stats and scale input
|
| 119 |
+
vstup, details = self._get_fighter_stats(f1, f2, verbose)
|
| 120 |
+
vstup_scaled = self._scale_input(vstup)
|
| 121 |
+
|
| 122 |
+
# Reshape for prediction
|
| 123 |
+
new_data = np.reshape(vstup_scaled, (1, 200, vstup_scaled.shape[1]))
|
| 124 |
+
|
| 125 |
+
# Make predictions both ways and average
|
| 126 |
+
pred_1 = self.model.predict(new_data, verbose=0)
|
| 127 |
+
|
| 128 |
+
# Get reverse prediction
|
| 129 |
+
vstup_rev, _ = self._get_fighter_stats(f2, f1, False)
|
| 130 |
+
vstup_rev_scaled = self._scale_input(vstup_rev)
|
| 131 |
+
new_data_rev = np.reshape(vstup_rev_scaled, (1, 200, vstup_rev_scaled.shape[1]))
|
| 132 |
+
pred_2 = self.model.predict(new_data_rev, verbose=0)
|
| 133 |
+
|
| 134 |
+
# Calculate final probability (as decimal between 0 and 1)
|
| 135 |
+
f1_prob = float(((1 - pred_1) + pred_2) / 2)
|
| 136 |
+
f2_prob = round(1 - f1_prob, 4)
|
| 137 |
+
f1_prob = round(f1_prob, 4)
|
| 138 |
+
|
| 139 |
+
# Add probability percentages to details if verbose
|
| 140 |
+
if verbose:
|
| 141 |
+
details["fighter1_win_percentage"] = f"{f1_prob * 100:.2f}%"
|
| 142 |
+
details["fighter2_win_percentage"] = f"{f2_prob * 100:.2f}%"
|
| 143 |
+
|
| 144 |
+
return f1_prob, f2_prob, details
|
| 145 |
+
|
| 146 |
+
except Exception as e:
|
| 147 |
+
print(f"Prediction failed: {str(e)}")
|
| 148 |
+
return None
|
preprocessing/UFC_data.ipynb
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
preprocessing/archiv/df_mode_old.csv
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
preprocessing/archiv/df_odds.csv
ADDED
|
@@ -0,0 +1,166 @@
|
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|
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|
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|
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|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
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|
|
|
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|
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|
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|
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|
|
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|
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|
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|
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|
|
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|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
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|
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|
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|
|
|
|
|
|
|
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|
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|
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|
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|
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|
|
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
fighter1,fighter2,odds_f1,odds_f2,bookmaker
|
| 2 |
+
Jesus Santos Aguilar,Tatsuro Taira,7.75,1.1,SuperBook
|
| 3 |
+
Jesus Santos Aguilar,Tatsuro Taira,7.5,1.1,Unibet
|
| 4 |
+
Jesus Santos Aguilar,Tatsuro Taira,7.5,1.1,Barstool Sportsbook
|
| 5 |
+
Jesus Santos Aguilar,Tatsuro Taira,9.0,1.08,LowVig.ag
|
| 6 |
+
Jesus Santos Aguilar,Tatsuro Taira,8.5,1.07,Bovada
|
| 7 |
+
Jesus Santos Aguilar,Tatsuro Taira,8.0,1.09,William Hill (US)
|
| 8 |
+
Jesus Santos Aguilar,Tatsuro Taira,7.5,1.1,SugarHouse
|
| 9 |
+
Jesus Santos Aguilar,Tatsuro Taira,7.5,1.1,BetRivers
|
| 10 |
+
Jesus Santos Aguilar,Tatsuro Taira,7.5,1.1,TwinSpires
|
| 11 |
+
Anshul Jubli,Jeka Saragih,1.83,1.97,Barstool Sportsbook
|
| 12 |
+
Anshul Jubli,Jeka Saragih,1.83,1.97,SugarHouse
|
| 13 |
+
Anshul Jubli,Jeka Saragih,1.83,2.0,William Hill (US)
|
| 14 |
+
Anshul Jubli,Jeka Saragih,1.9,1.92,LowVig.ag
|
| 15 |
+
Anshul Jubli,Jeka Saragih,1.83,1.97,BetRivers
|
| 16 |
+
Anshul Jubli,Jeka Saragih,1.83,2.0,SuperBook
|
| 17 |
+
Anshul Jubli,Jeka Saragih,1.83,1.97,Unibet
|
| 18 |
+
Anshul Jubli,Jeka Saragih,1.83,1.97,TwinSpires
|
| 19 |
+
Anshul Jubli,Jeka Saragih,1.87,1.95,DraftKings
|
| 20 |
+
Anshul Jubli,Jeka Saragih,1.87,1.95,Bovada
|
| 21 |
+
Denis Tiuliulin,Jun Yong Park,2.8,1.48,LowVig.ag
|
| 22 |
+
Denis Tiuliulin,Jun Yong Park,2.65,1.51,William Hill (US)
|
| 23 |
+
Denis Tiuliulin,Jun Yong Park,2.75,1.49,DraftKings
|
| 24 |
+
Denis Tiuliulin,Jun Yong Park,2.75,1.5,SuperBook
|
| 25 |
+
Denis Tiuliulin,Jun Yong Park,2.7,1.48,Bovada
|
| 26 |
+
Denis Tiuliulin,Jun Yong Park,2.63,1.49,BetRivers
|
| 27 |
+
Denis Tiuliulin,Jun Yong Park,2.63,1.49,SugarHouse
|
| 28 |
+
Denis Tiuliulin,Jun Yong Park,2.63,1.49,TwinSpires
|
| 29 |
+
Denis Tiuliulin,Jun Yong Park,2.63,1.49,Unibet
|
| 30 |
+
Denis Tiuliulin,Jun Yong Park,2.63,1.49,Barstool Sportsbook
|
| 31 |
+
Hyun Sung Park,Seung Guk Choi,1.51,2.55,Barstool Sportsbook
|
| 32 |
+
Hyun Sung Park,Seung Guk Choi,1.51,2.55,SugarHouse
|
| 33 |
+
Hyun Sung Park,Seung Guk Choi,1.5,2.7,William Hill (US)
|
| 34 |
+
Hyun Sung Park,Seung Guk Choi,1.51,2.55,TwinSpires
|
| 35 |
+
Hyun Sung Park,Seung Guk Choi,1.51,2.55,BetRivers
|
| 36 |
+
Hyun Sung Park,Seung Guk Choi,1.51,2.55,Unibet
|
| 37 |
+
Hyun Sung Park,Seung Guk Choi,1.5,2.55,Bovada
|
| 38 |
+
Hyun Sung Park,Seung Guk Choi,1.55,2.57,LowVig.ag
|
| 39 |
+
Hyun Sung Park,Seung Guk Choi,1.53,2.6,DraftKings
|
| 40 |
+
Jeongyoung Lee,Yi Zha,1.42,3.0,William Hill (US)
|
| 41 |
+
Jeongyoung Lee,Yi Zha,1.4,3.0,SugarHouse
|
| 42 |
+
Jeongyoung Lee,Yi Zha,1.4,3.0,TwinSpires
|
| 43 |
+
Jeongyoung Lee,Yi Zha,1.4,3.0,BetRivers
|
| 44 |
+
Jeongyoung Lee,Yi Zha,1.4,3.0,Barstool Sportsbook
|
| 45 |
+
Jeongyoung Lee,Yi Zha,1.4,3.0,Unibet
|
| 46 |
+
Jeongyoung Lee,Yi Zha,1.4,3.11,LowVig.ag
|
| 47 |
+
Ji Yeon Kim,Mandy Böhm,1.38,3.25,SuperBook
|
| 48 |
+
Ji Yeon Kim,Mandy Böhm,1.35,3.2,Unibet
|
| 49 |
+
Ji Yeon Kim,Mandy Böhm,1.35,3.2,Barstool Sportsbook
|
| 50 |
+
Ji Yeon Kim,Mandy Böhm,1.39,3.15,LowVig.ag
|
| 51 |
+
Ji Yeon Kim,Mandy Böhm,1.39,3.15,DraftKings
|
| 52 |
+
Ji Yeon Kim,Mandy Böhm,1.36,3.12,Bovada
|
| 53 |
+
Ji Yeon Kim,Mandy Böhm,1.38,3.1,William Hill (US)
|
| 54 |
+
Ji Yeon Kim,Mandy Böhm,1.35,3.2,SugarHouse
|
| 55 |
+
Ji Yeon Kim,Mandy Böhm,1.35,3.2,BetRivers
|
| 56 |
+
Ji Yeon Kim,Mandy Böhm,1.35,3.2,TwinSpires
|
| 57 |
+
Adam Fugitt,Yusaku Kinoshita,3.4,1.32,Bovada
|
| 58 |
+
Adam Fugitt,Yusaku Kinoshita,3.2,1.35,SugarHouse
|
| 59 |
+
Adam Fugitt,Yusaku Kinoshita,3.2,1.35,TwinSpires
|
| 60 |
+
Adam Fugitt,Yusaku Kinoshita,3.7,1.31,LowVig.ag
|
| 61 |
+
Adam Fugitt,Yusaku Kinoshita,3.2,1.35,Barstool Sportsbook
|
| 62 |
+
Adam Fugitt,Yusaku Kinoshita,3.2,1.35,BetRivers
|
| 63 |
+
Adam Fugitt,Yusaku Kinoshita,3.3,1.37,SuperBook
|
| 64 |
+
Adam Fugitt,Yusaku Kinoshita,3.2,1.35,Unibet
|
| 65 |
+
Adam Fugitt,Yusaku Kinoshita,3.5,1.33,DraftKings
|
| 66 |
+
Blagoy Ivanov,Marcin Tybura,2.3,1.67,SuperBook
|
| 67 |
+
Blagoy Ivanov,Marcin Tybura,2.26,1.69,LowVig.ag
|
| 68 |
+
Blagoy Ivanov,Marcin Tybura,2.25,1.67,Bovada
|
| 69 |
+
Blagoy Ivanov,Marcin Tybura,2.25,1.64,BetRivers
|
| 70 |
+
Blagoy Ivanov,Marcin Tybura,2.25,1.64,SugarHouse
|
| 71 |
+
Blagoy Ivanov,Marcin Tybura,2.25,1.64,TwinSpires
|
| 72 |
+
Blagoy Ivanov,Marcin Tybura,2.25,1.64,Unibet
|
| 73 |
+
Blagoy Ivanov,Marcin Tybura,2.25,1.64,Barstool Sportsbook
|
| 74 |
+
Da Un Jung,Devin Clark,1.42,3.0,SuperBook
|
| 75 |
+
Da Un Jung,Devin Clark,1.52,2.68,LowVig.ag
|
| 76 |
+
Da Un Jung,Devin Clark,1.47,2.85,DraftKings
|
| 77 |
+
Da Un Jung,Devin Clark,1.45,2.78,Bovada
|
| 78 |
+
Da Un Jung,Devin Clark,1.42,2.88,BetRivers
|
| 79 |
+
Da Un Jung,Devin Clark,1.42,2.88,SugarHouse
|
| 80 |
+
Da Un Jung,Devin Clark,1.42,2.88,TwinSpires
|
| 81 |
+
Da Un Jung,Devin Clark,1.42,2.88,Unibet
|
| 82 |
+
Da Un Jung,Devin Clark,1.42,2.88,Barstool Sportsbook
|
| 83 |
+
Derrick Lewis,Sergey Spivak,2.9,1.45,SuperBook
|
| 84 |
+
Derrick Lewis,Sergey Spivak,2.95,1.43,DraftKings
|
| 85 |
+
Derrick Lewis,Sergey Spivak,2.9,1.38,Bovada
|
| 86 |
+
Derrick Lewis,Sergey Spivak,2.85,1.43,BetRivers
|
| 87 |
+
Derrick Lewis,Sergey Spivak,2.85,1.43,SugarHouse
|
| 88 |
+
Derrick Lewis,Sergey Spivak,2.85,1.43,TwinSpires
|
| 89 |
+
Derrick Lewis,Sergey Spivak,2.85,1.43,Unibet
|
| 90 |
+
Derrick Lewis,Sergey Spivak,2.85,1.43,Barstool Sportsbook
|
| 91 |
+
Dooho Choi,Kyle Nelson,1.54,2.65,SuperBook
|
| 92 |
+
Dooho Choi,Kyle Nelson,1.55,2.57,LowVig.ag
|
| 93 |
+
Dooho Choi,Kyle Nelson,1.53,2.6,DraftKings
|
| 94 |
+
Dooho Choi,Kyle Nelson,1.53,2.55,Bovada
|
| 95 |
+
Dooho Choi,Kyle Nelson,1.55,2.48,BetRivers
|
| 96 |
+
Dooho Choi,Kyle Nelson,1.55,2.48,SugarHouse
|
| 97 |
+
Dooho Choi,Kyle Nelson,1.55,2.48,TwinSpires
|
| 98 |
+
Dooho Choi,Kyle Nelson,1.55,2.48,Unibet
|
| 99 |
+
Dooho Choi,Kyle Nelson,1.55,2.48,Barstool Sportsbook
|
| 100 |
+
Blake Bilder,Shane Young,2.0,1.83,DraftKings
|
| 101 |
+
Blake Bilder,Shane Young,1.97,1.81,MyBookie.ag
|
| 102 |
+
Blake Bilder,Shane Young,2.0,1.83,SuperBook
|
| 103 |
+
Blake Bilder,Shane Young,2.05,1.8,LowVig.ag
|
| 104 |
+
Blake Bilder,Shane Young,1.97,1.82,Barstool Sportsbook
|
| 105 |
+
Blake Bilder,Shane Young,1.97,1.82,TwinSpires
|
| 106 |
+
Blake Bilder,Shane Young,1.97,1.82,SugarHouse
|
| 107 |
+
Blake Bilder,Shane Young,1.97,1.82,BetRivers
|
| 108 |
+
Blake Bilder,Shane Young,1.97,1.82,Unibet
|
| 109 |
+
Justin Tafa,Parker Porter,1.69,2.25,LowVig.ag
|
| 110 |
+
Justin Tafa,Parker Porter,1.71,2.2,DraftKings
|
| 111 |
+
Justin Tafa,Parker Porter,1.66,2.19,MyBookie.ag
|
| 112 |
+
Justin Tafa,Parker Porter,1.69,2.25,SuperBook
|
| 113 |
+
Justin Tafa,Parker Porter,1.67,2.2,Barstool Sportsbook
|
| 114 |
+
Justin Tafa,Parker Porter,1.67,2.2,SugarHouse
|
| 115 |
+
Justin Tafa,Parker Porter,1.67,2.2,TwinSpires
|
| 116 |
+
Justin Tafa,Parker Porter,1.67,2.2,BetRivers
|
| 117 |
+
Justin Tafa,Parker Porter,1.67,2.2,Unibet
|
| 118 |
+
Jack Della Maddalena,Randy Brown,1.33,3.45,LowVig.ag
|
| 119 |
+
Jack Della Maddalena,Randy Brown,1.33,3.55,DraftKings
|
| 120 |
+
Jack Della Maddalena,Randy Brown,1.3,3.41,MyBookie.ag
|
| 121 |
+
Jack Della Maddalena,Randy Brown,1.32,3.6,SuperBook
|
| 122 |
+
Jack Della Maddalena,Randy Brown,1.29,3.65,Barstool Sportsbook
|
| 123 |
+
Jack Della Maddalena,Randy Brown,1.29,3.65,SugarHouse
|
| 124 |
+
Jack Della Maddalena,Randy Brown,1.29,3.65,TwinSpires
|
| 125 |
+
Jack Della Maddalena,Randy Brown,1.29,3.65,BetRivers
|
| 126 |
+
Jack Della Maddalena,Randy Brown,1.29,3.65,Unibet
|
| 127 |
+
Josh Emmett,Yair Rodriguez,2.35,1.65,LowVig.ag
|
| 128 |
+
Josh Emmett,Yair Rodriguez,2.35,1.65,DraftKings
|
| 129 |
+
Josh Emmett,Yair Rodriguez,2.26,1.62,MyBookie.ag
|
| 130 |
+
Josh Emmett,Yair Rodriguez,2.35,1.65,SuperBook
|
| 131 |
+
Josh Emmett,Yair Rodriguez,2.32,1.61,TwinSpires
|
| 132 |
+
Josh Emmett,Yair Rodriguez,2.32,1.61,Barstool Sportsbook
|
| 133 |
+
Josh Emmett,Yair Rodriguez,2.32,1.61,BetRivers
|
| 134 |
+
Josh Emmett,Yair Rodriguez,2.32,1.61,Unibet
|
| 135 |
+
Josh Emmett,Yair Rodriguez,2.32,1.61,SugarHouse
|
| 136 |
+
Alex Volkanovski,Islam Makhachev,3.95,1.28,LowVig.ag
|
| 137 |
+
Alex Volkanovski,Islam Makhachev,3.75,1.28,Barstool Sportsbook
|
| 138 |
+
Alex Volkanovski,Islam Makhachev,3.75,1.28,BetRivers
|
| 139 |
+
Alex Volkanovski,Islam Makhachev,3.75,1.28,Unibet
|
| 140 |
+
Alex Volkanovski,Islam Makhachev,3.75,1.28,TwinSpires
|
| 141 |
+
Alex Volkanovski,Islam Makhachev,3.75,1.28,SugarHouse
|
| 142 |
+
Alex Volkanovski,Islam Makhachev,4.0,1.27,DraftKings
|
| 143 |
+
Alex Volkanovski,Islam Makhachev,3.62,1.28,MyBookie.ag
|
| 144 |
+
Alex Volkanovski,Islam Makhachev,3.9,1.29,SuperBook
|
| 145 |
+
Alexa Grasso,Valentina Shevchenko,5.1,1.17,Barstool Sportsbook
|
| 146 |
+
Alexa Grasso,Valentina Shevchenko,5.1,1.17,TwinSpires
|
| 147 |
+
Alexa Grasso,Valentina Shevchenko,5.25,1.17,LowVig.ag
|
| 148 |
+
Alexa Grasso,Valentina Shevchenko,5.1,1.17,SugarHouse
|
| 149 |
+
Alexa Grasso,Valentina Shevchenko,5.1,1.17,BetRivers
|
| 150 |
+
Ciryl Gane,Jon Jones,2.15,1.74,LowVig.ag
|
| 151 |
+
Ciryl Gane,Jon Jones,2.05,1.8,DraftKings
|
| 152 |
+
Ciryl Gane,Jon Jones,2.1,1.73,Barstool Sportsbook
|
| 153 |
+
Ciryl Gane,Jon Jones,2.1,1.73,BetRivers
|
| 154 |
+
Ciryl Gane,Jon Jones,2.1,1.73,SugarHouse
|
| 155 |
+
Ciryl Gane,Jon Jones,2.1,1.73,TwinSpires
|
| 156 |
+
Kamaru Usman,Leon Edwards,1.41,2.85,Barstool Sportsbook
|
| 157 |
+
Kamaru Usman,Leon Edwards,1.41,2.85,BetRivers
|
| 158 |
+
Kamaru Usman,Leon Edwards,1.41,2.85,SugarHouse
|
| 159 |
+
Kamaru Usman,Leon Edwards,1.41,2.85,TwinSpires
|
| 160 |
+
Kamaru Usman,Leon Edwards,1.41,3.05,DraftKings
|
| 161 |
+
Alex Pereira,Israel Adesanya,2.14,1.71,Barstool Sportsbook
|
| 162 |
+
Alex Pereira,Israel Adesanya,2.14,1.71,BetRivers
|
| 163 |
+
Alex Pereira,Israel Adesanya,2.14,1.71,TwinSpires
|
| 164 |
+
Alex Pereira,Israel Adesanya,2.14,1.71,SugarHouse
|
| 165 |
+
Alex Pereira,Israel Adesanya,2.35,1.65,DraftKings
|
| 166 |
+
Alex Pereira,Israel Adesanya,2.35,1.65,LowVig.ag
|
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preprocessing/archiv/fight_result.csv
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preprocessing/archiv/fight_with_stats.csv
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preprocessing/archiv/fight_with_stats_precomp.csv
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preprocessing/archiv/fighter_details.csv
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preprocessing/archiv/fighter_total_stats.csv
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preprocessing/archov/df_model.csv
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preprocessing/archov/df_skills.csv
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preprocessing/archov/fight_result.csv
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preprocessing/archov/fight_with_stats.csv
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preprocessing/archov/fight_with_stats_precomp1.csv
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